Abstract
Background
Knee pain associated with osteoarthritis is a significant contributor to decreased physical function. Recent evidence supports the inter-individual heterogeneity associated with knee pain presentation, but whether there is similar heterogeneity in physical performance among these individuals has not been previously examined. The aim of the present study was to characterize the variability in physical performance profiles and the pain evoked by their performance (i.e., movement-evoked pain).
Methods
In a secondary analysis of the community-based study Understanding Pain and Limitations in Osteoarthritic Disease (UPLOAD), individuals (n=270) completed functional, pain, psychological, and somatosensory assessments. Hierarchical cluster analysis was used to derive physical function profiles that were subsequently compared across several clinical, psychological and experimental pain measures.
Results
Our results support the hypothesis that among persons with knee OA pain, three different physical performance profiles exist with varying degrees of movement-evoked pain. Even as all three groups experienced moderate to severe levels of spontaneous knee pain, those individuals with the most severe movement-evoked pain and lowest physical functional performance also had the least favorable psychological characteristics along with increased mechanical pain sensitivity and temporal summation.
Conclusions
Our findings support the need for the assessment and consideration of movement-evoked pain during physical performance tasks as these have the potential to increase the value of functional and pain assessments clinically. The identification of the mechanisms driving pain burden within homogeneous groups of individuals will ultimately allow for targeted implementation of treatments consistent with a biopsychosocial model of pain.
Keywords: pain, physical function, inter-individual variability
Introduction
The incidence of osteoarthritis (OA) is dramatically increasing worldwide as the aging population grows. In particular, the knee is the most commonly affected joint where multiple cellular and molecular mechanisms underlie loss of synovial tissue structure and function ultimately leading to reduced physical functioning and pain (Mobasheri et al., 2015; Musumeci et al., 2015; Jinks et al. 2007; Neogi et al. 2009). Lower self-reported and performance-based physical function has been consistently observed in older adults with knee pain (Hopman-Rock et al. 1996; Sharma et al. 2003). Indeed, pain-associated reduction in physical function is a strong predictor of future disability and dependency in elderly people (Zakoscielna & Parmelee 2013).
Recent evidence demonstrates considerable inter-individual heterogeneity among people with knee pain across a number of clinical, experimental and psychological variables (Cruz-Almeida et al. 2013; Cardoso et al. 2016; Frey-Law et al. 2016). There is likely similar heterogeneity in physical functional performance among individuals with knee pain that accounts for distinct functional trajectories (i.e., get worse or recover over time) (van Dijk et al. 2006). While it is common to classify individuals into categories of high versus low physical function, a more sophisticated approach would consider patterns of responses across multiple functional domains. Additionally, common measures of physical performance do not routinely assess pain during task performance, i.e. movement-evoked pain, which is likely one of the drivers of the observed physical performance outcomes. Although abundant evidence exists that pain impacts physical functional performance, no studies to date have examined potential differences in physical functional performance and movement-evoked pain among persons with knee OA pain. Therefore, the primary aims of the present study were: 1) to identify subgroups in persons with knee pain based on physical performance and movement evoked-pain measures, and 2) to compare these subgroups with respect to clinical pain, as well as psychological and somatosensory function measures. Identification of subgroups among persons with knee OA would ultimately allow for targeted treatment approaches.
Methods
This is a secondary data analysis including 270 individuals with knee pain who participated in the community-based study Understanding Pain and Limitations in Osteoarthritic Disease (UPLOAD) at the University of Florida (UF) and the University of Alabama at Birmingham (UAB). The aim of the parent study was to understand ethnic differences in pain and functional limitations in persons with knee pain. The sample was between 45 and 85 years of age who identified as either African American (AA) or non-Hispanic whites (NHW). Participants had knee postero-anterior and lateral radiographs to assess severity of radiographic OA (i.e., KL score). A detailed description of the screening, inclusion/exclusion criteria has been reported previously (King et al. 2013; Cruz-Almeida et al., 2014). Participants were excluded if they: 1) had cognitive impairment; 2) used opioids on a daily basis; 3) were hospitalized for a psychiatric illness in the preceding year; 4) had a history of acute myocardial infarction, heart failure or uncontrolled hypertension (BP >150/95 mm Hg); 5) had bilateral prosthetic knee replacements or other clinically significant surgery to the affected knee; 6) had peripheral neuropathy; 7) had systemic diseases including rheumatoid arthritis, systemic lupus erythematosus or fibromyalgia. After consent, subjects underwent a general health assessment (HAS) session followed by a quantitative sensory testing (QST) session no more than 4 weeks apart. During the HAS, participants completed questionnaires (detailed below) and physical function assessments and a physician/nurse practitioner conducted a health history/examination including weight and height measurements for BMI calculation. During the QST, a multimodal experimental pain battery was administered (details previously reported) (Cruz-Almeida et al. 2014; King et al. 2013). Both UF and UAB IRBs approved the study (IRB# 201400209).
Physical Function
Short Physical Performance Battery (SPPB)
The SPPB consists of three measures of lower-extremity function: standing balance, 4-meter walking speed, and ability to rise from a chair. Participants were asked for an overall numerical pain rating for their knee using a visual analogue scale (VAS) of 0–100, where 0 = no pain sensation and 100 = the most intense pain sensation imaginable. These measures have been standardized and are widely used in older populations (Guralnik et al. 1995).
QST
Heat Pain Threshold (HPT)
Stimulation was administered by a computer-controlled Medoc PATHWAY Pain & Sensory Evaluation System with a 16×16 mm Advanced Thermal stimulator. HPT was assessed on the most painful knee and ipsilateral ventral forearm. HPT trials started with the thermode at 32°C increasing at 0.5°C/s until the participant pressed a button indicating the sensation “first became painful.” HPT was repeated 3 times and averaged for analysis.
Temporal Summation of Heat Pain
Heat stimuli were applied to the most painful knee and ipsilateral forearm using the CHEPS thermode of the PATHWAY system. The experimenter moved the thermode between trials to avoid sensitization/habituation of cutaneous nociceptors. Participants were asked to rate their heat pain using a VAS (0–100). Stimulations lasted <1 second with a 2.5-second inter-stimulus interval with target temperature of 44°C. If a subject gave a rating of 100 the procedure was stopped. The first pain rating was subtracted from the fifth pain rating as the change score.
Pressure Pain Threshold (PPT)
PPT was assessed on the most affected knee, the ipsilateral quadriceps, extensor carpi radialis longus and trapezius. Order of testing was counterbalanced and randomized. For all test sites, a handheld digital pressure algometer (AlgoMed; Medoc) was applied at a constant rate of 30kPa/s. Participants were instructed to press a button when the pressure sensation “first became painful”. PPTs were repeated 3 times on each site to create a mean PPT for that site. The maximum pressure for the knee was 600kPa and 1000kPa for other sites. Maximum pressures were based on safety considerations for our knee pain participants. For individuals reaching maximum pressure levels without reporting pain, a value of 600/1000 was assigned.
Punctate Pain
Subjects underwent a punctate mechanical stimulation procedure using a calibrated nylon monofilament with 300 grams of force. Punctate mechanical testing was performed on the patella of the index knee and the back of the ipsilateral hand, in randomized order. Participants were instructed to provide a verbal pain rating on a 0–100 scale after a single contact. The single pain ratings were averaged together separately at knee and hand dorsum).
Immediately following the single stimulus, a series of 10 stimuli were administered and participants provided a verbal rating of the greatest pain intensity experienced. Two series of stimulations were administered at a rate of one contact per second. The ratings were averaged separately by site. The averages of the single pain ratings were subtracted from the averages of the 10 trials to calculate temporal summation at each location.
Cold Pressor Task (CPT)
Participants were asked to submerge their right hand up to the wrist in cold water during 3 separate trials of 16°C, 12°C, and 8°C, separated by 10-minute breaks. Temperatures were maintained (+0.1°C) by a refrigeration unit (Neslab) that constantly circulated water to prevent warming around the immersed hand. The time the participants could keep their hand in the water was recorded for each individual temperature (seconds).
Clinical and Psychosocial Assessments
Graded Chronic Pain Scale (GCPS)
The GCPS measures knee pain severity over the past 6 months. The GCPS contains 7-items related to pain intensity and pain-related interference with activities. We used pain frequency and characteristic pain intensity scores (Von Korff et al. 1992).
Number of painful sites
Participants indicated areas besides the knee where they felt pain including head, neck, shoulders, chest, stomach, upper and lower back, arms, hands, legs and feet. The total number of sites was used for analysis.
Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC)
The WOMAC assesses knee OA symptoms in the preceding 48 hours, including pain, stiffness and physical function (Bellamy et al. 1988). Higher scores indicate greater levels of pain, stiffness, and functional limitations.
Coping Strategies Questionnaire-Revised (CSQ-R)
The CSQ-R measures pain-related active and passive coping techniques (Robinson et al. 1997). The CSQ’s catastrophizing subscale has been validated and is commonly used to assess catastrophizing (Sullivan et al. 2001).
Pain Vigilance and Awareness Questionnaire (PVAQ)
The PVAQ assesses attention to pain, as well as preoccupation and vigilance related to pain over the past few weeks (McCracken 1997). Greater scores represent greater pain vigilance (Roelofs et al. 2003).
The Center for Epidemiologic Studies Depression Scale (CES-D)
The CES-D measures the frequency of depressive symptoms during the preceding week (Radloff 1977). Higher scores indicate greater levels of depressive symptomatology.
Positive and Negative Affect Scale (PANAS)
The PANAS is comprised of 20-items rated on a 5-point scale (Watson et al. 1988; Crawford & Henry 2004). Higher scores on positive items indicate higher positive affect, while higher scores on negative items indicate higher negative affect.
Statistical Methods
Cluster Analysis of SPPB Measures
To identify homogenous subgroups, we entered the 3 SPPB subscales (i.e., Balance, Gait, Chair Stands) along with their movement-evoked pain ratings into a hierarchical cluster analysis using Ward's clustering method with squared Euclidean distances. The optimal number of clusters was determined by examining the agglomeration coefficients and analysis of the dendogram. We used ANOVAs to assess the internal validity of the final cluster solution on the raw variables.
External Validation of the Cluster Solution
The empirically derived clusters were compared across the total SPPB score, clinical pain, psychological and somatosensory function measures using ANCOVA procedures with Bonferroni post-hoc adjustments. Race and study site were included as covariates given their differential distribution across the clusters. Chi-square analyses were used to compare the clusters on categorical data. Normality assumption was determined by a combination of the Shapiro Wilk test and examination of the Quantile-Quantile (Q-Q) Plots. Alpha was set to 0.05 for all hypothesis testing. All analyses were conducted in IBM-SPSS24 software for MacOS.
Results
Our study sample was mostly female (63.1%) and AA (56.3%) with an average age of 57 years (45–85 years old). Three clusters emerged and were significantly different across clustering variables. Table 2 details the variables used for clustering and how they were significantly different between the clusters, (p<0.05). Cluster 1 was the largest (n=143) and consisted of individuals with the highest physical function and minimal performance-evoked pain, Cluster 2 (n=101) consisted of individuals with moderate physical function and mild performance-evoked pain and Cluster 3 was a small group of individuals (n=24) with the lowest functional performance along with severe performance-evoked pain. Clusters differed significantly in their race composition and recruitment study site (p<0.05), but not in age, BMI, sex, KL scores or educational attainment (Table 1, p>0.05).
Table 2.
Physical functional measures across the clusters.
| Cluster 1 Highest Function Minimal Movement-Evoked Pain (n=145) |
Cluster 2 Moderate Function Mild Movement-Evoked Pain (n=101) |
Cluster 3 Lowest Function Severe Movement-Evoked Pain (n=24) |
p-value | |
|---|---|---|---|---|
| Chair Stand Score, mean ± SD | 2.9 ± 1.1 | 2.0 ± 1.3 | 1.5 ± 1.1 | <0.0001 |
| Pain Chair Stand, mean ± SD | 4.5 ± 5.4 | 31.7 ± 17.8 | 75.7 ± 25.2 | <0.0001 |
| Gait Score, mean ± SD | 3.7 ± 0.7 | 3.6 ± 0.8 | 3.0 ± 1.0 | 0.001 |
| Pain Gait, mean ± SD | 2.2 ± 3.5 | 24.4 ± 15.5 | 73.8 ± 16.0 | <0.0001 |
| Balance, mean ± SD | 3.9 ± 0.3 | 3.8 ± 0.6 | 3.6 ± 0.7 | 0.012 |
| Pain Balance, mean ± SD | 1.8 ± 2.6 | 22.3 ± 14.2 | 72.7 ± 16.8 | <0.0001 |
| SPPB Total Score* | 10.5 ± 1.5 | 9.4 ± 1.9 | 8.0 ± 2.0 | <0.0001 |
SPPB Total Score was NOT entered into the clustering procedure
Table 1.
Demographic & socioeconomic measures across the clusters.
| Cluster 1 (n=145) |
Cluster 2 (n=101) |
Cluster 3 (n=24) |
P | |
|---|---|---|---|---|
| Age, mean ± SD years | 57.2 ± 7.4 | 55.9 ± 7.6 | 56.3 ± 7.4 | 0.402 |
| BMI, mean ± SD kg/m2 | 30.9 ± 7.1 | 32.0 ± 7.6 | 33.9 ± 9.7 | 0.151 |
| Sex, no. (%), X2 | 0.191 | |||
| Female | 98 (67.6) | 57 (56.4) | 16 (66.7) | |
| Male | 47 (32.4) | 44 (43.6) | 8 (33.3) | |
| Race, no. (%), X2 | <0.0001 | |||
| African American | 71 (49.0) | 67 (66.7) | 20 (83.3) | |
| Non-Hispanic White | 74 (51.0) | 34 (33.3) | 4 (16.7) | |
| Right Knee KL Score, no. (%), X2 | 0.208 | |||
| 0 | 76 (57.1) | 43 (47.8) | 11 (45.8) | |
| 1 | 18 (13.5) | 16 (17.8) | 3 (12.5) | |
| 2 | 20 (15.0) | 8 (8.9) | 3 (12.5) | |
| 3 | 14 (10.5) | 11 (12.2) | 4 (16.7) | |
| 4 | 5 (3.8) | 12 (13.3) | 3 (12.5) | |
| Left Knee KL Score, no. (%), X2 | 0.114 | |||
| 0 | 80 (60.2) | 44 (48.4) | 9 (37.5) | |
| 1 | 17 (12.8) | 21 (23.1) | 5 (20.8) | |
| 2 | 15 (11.3) | 13 (14.3) | 2 (8.3) | |
| 3 | 15 (11.3) | 11 (12.1) | 5 (20.8) | |
| 4 | 6 (4.5) | 2 (2.2) | 3 (12.5) | |
| Education, no (%), X2 | 0.163 | |||
| High school or less | 58 (40.0) | 57 (56.4) | 12 (50.0) | |
| 2 years of college | 33 (22.8) | 23 (22.8) | 6 (25.0) | |
| Bachelor's degree and above | 54 (37.2) | 21 (20.8) | 6 (25.0) | |
| Site, no (%), X2 | <0.0001 | |||
| University of Florida | 75 (54.7) | 73 (76.8) | 19 (82.6) | |
| University of Alabama at Birmingham | 62 (45.3) | 22 (23.2) | 4 (17.4) |
Clusters also differed significantly across most clinical and psychological measures, even after adjusting for race and study site (Table 3, p<0.05). Individuals in Cluster 3 had significantly greater spontaneous pain intensity and frequency during the past 6 months, more painful sites and higher WOMAC scores than individuals in Cluster 1. Similarly, participants in Cluster 3 reported significantly greater depressive symptomatology, greater use of active and passive coping strategies, more catastrophizing, pain hypervigilance and negative affect than individuals in Cluster 1. However, all three clusters reported similar levels of positive affect (p>0.05).
Table 3.
Clinical pain and psychological measures across the clusters adjusted for race and study site.
| Cluster 1 Higher Function Minimal Movement-Evoked Pain (n=145) |
Cluster 2 Moderate Function Mild Movement- Evoked Pain (n=101) |
Cluster 3 Lower Function Severe Movement- Evoked Pain (n=24) |
Adju sted p- value |
|
|---|---|---|---|---|
| Characteristic Pain Intensity, mean ± SD | 41.8 ± 20.0 | 57.5 ± 18.2 | 79.2 ± 11.6 | <0.0001 |
| WOMAC-Pain, mean ± SD | 5.4 ± 3.4 | 8.6 ± 3.5 | 13.2 ± 3.3 | <0.0001 |
| WOMAC- Stiffness, mean ± SD | 2.8 ± 0.7 | 3.9 ± 0.8 | 5.5 ± 1.0 | <0.0001 |
| WOMAC-Function, mean ± SD | 17.8 ± 11.9 | 27.6 ± 12.6 | 42.0 ± 10.5 | <0.0001 |
| # of Pain Sites, mean ± SD | 4.5 ± 3.8 | 5.8 ± 3.7 | 9.0 ± 4.8 | <0.0001 |
| # of Pain Days Past 6 mo., mean ± SD | 7.5 ± 14.8 | 20.7 ± 38.9 | 40.3 ± 56.9 | <0.0001 |
| CES-D, mean ± SD | 8.2 ± 6.7 | 10.8 ± 7.9 | 12.9 ± 7.2 | 0.003 |
| CSQ- Active Coping, mean ± SD | 2.7 ± 0.9 | 3.2 ± 0.9 | 3.4 ± 1.0 | 0.001 |
| CSQ- Passive Coping, mean ± SD | 2.8 ± 1.2 | 2.9 ± 1.1 | 3.6 ± 1.0 | 0.004 |
| CSQ- Catastrophizing, mean ± SD | 1.5 ± 0.9 | 1.7 ± 1.1 | 2.4 ± 1.2 | <0.0001 |
| PVAQ, mean ± SD | 44.6 ± 14.7 | 45.4 ± 13.7 | 56.3 ± 10.3 | <0.0001 |
| Positive Affect, mean ± SD | 35.4 ± 7.5 | 35.6 ± 7.8 | 36.4 ± 8.7 | 0.832 |
| Negative Affect, mean ± SD | 13.7 ± 4.6 | 15.7 ± 6.5 | 15.1 ± 6.5 | 0.050 |
Clusters also differed significantly across most QST measures even after adjusting for race and study site (Table 4, p<0.05). Individuals in Cluster 3 had significantly lower pressure and cold pain sensitivity and higher punctate pain sensitivity at the knee and at other distal sites compared to individuals in Cluster 1. Individuals in Cluster 3 also experienced greater temporal summation of heat and punctate pain than individuals in Cluster 1.
Table 4.
QST measures across clusters adjusted for race and study site.
| Cluster 1 Higher Function Minimal Movement- Evoked Pain (n=145) |
Cluster 2 Moderate Function Mild Movement- Evoked Pain (n=101) |
Cluster 3 Lower Function Severe Movement- Evoked Pain (n=24) |
Adjusted p-value |
|
|---|---|---|---|---|
| PPT- Medial Knee, mean ± SD | 293 ± 159 | 275 ± 161 | 191 ± 118 | 0.014 |
| PPT- Lateral Knee, mean ± SD | 312 ± 173 | 293 ± 164 | 208 ± 105 | 0.019 |
| PPT- Arm, mean ± SD | 247 ± 169 | 248 ± 170 | 152 ± 74 | 0.028 |
| PPT- Trapezius, mean ± SD | 275 ± 175 | 255 ± 172 | 189 ± 89 | 0.070 |
| PPT- Quadriceps, mean ± SD | 434 ± 229 | 405 ± 218 | 311 ± 142 | 0.043 |
| Punctate Pain, Hand, mean ± SD | 11.9 ± 16.7 | 11.0 ± 14.9 | 20.4 ± 24.2 | 0.044 |
| Punctate Pain, Knee, mean ± SD | 16.1 ± 19.8 | 13.9 ± 16.6 | 32.6 ± 28.5 | <0.0001 |
| CPT-16°C, mean ± SD seconds | 34.0 ± 19.3 | 33.7 ± 17.8 | 29.6 ± 16.1 | 0.587 |
| CPT-12°C, mean ± SD seconds | 54.8 ± 11.9 | 49.5 ± 15.9 | 49.0 ± 15.5 | 0.008 |
| CPT-8°C, mean ± SD seconds | 48.6 ± 16.7 | 41.6 ± 20.5 | 39.0 ± 19.3 | 0.004 |
| HPT- Arm, mean ± SD | 41.7 ± 3.3 | 41.7 ± 3.3 | 41.1 ± 3.5 | 0.710 |
| HPT- Knee, mean ± SD | 42.1 ± 3.1 | 41.7 ± 3.5 | 41.1 ± 3.9 | 0.334 |
| Heat TS- Knee, mean ± SD | 0.3 ± 14.0 | 0.6 ± 14.3 | 8.7 ± 20.1 | 0.045 |
| Punctate TS- Arm, mean ± SD | 13.3 ± 16.1 | 19.4 ± 22.6 | 24.1 ± 20.5 | 0.009 |
| Punctate TS- Knee, mean ± SD | 18.4 ± 18.0 | 23.6 ± 21.5 | 25.2 ± 18.0 | 0.084 |
Discussion
We sought to identify physical performance profiles among a sample of community-dwelling individuals with knee pain and to determine the relationship between these profiles with clinical, psychological and somatosensory function measures. While ample evidence demonstrates decreased physical performance in individuals with versus without knee pain, our finding of functional subgroups among individuals with knee pain is novel. In particular, clinically meaningful differences in functional performance (Perera et al. 2006) were highly associated with the severity of the pain evoked by the functional tasks (i.e., performance-associated pain, movement-evoked pain). The subgroup with the highest functional performance across all tasks experienced minimal movement-evoked pain, while the lowest functional group across all tasks experienced the most severe movement-evoked pain. Movement-evoked pain measures enhance functional assessments by providing additional insight regarding the adverse effects of movement rather than simply measuring the functional performance alone. Recent evidence suggests that movement-evoked pain might represent a dimension of the pain experience that is more disability-relevant than spontaneous pain (Mankovsky-Arnold et al. 2014). This is further supported by our findings. While all three groups experienced moderate to severe levels of spontaneous knee pain during the past six months, those with the most severe movement-evoked pain and lowest physical function also experienced more frequent pain at multiple body sites. This is consistent with evidence from the MOBILIZE Boston study where multisite pain was a strong predictor of poorer lower body function (Eggermont et al. 2009). In addition, pain at the knee was the joint location most strongly associated with poor function (Eggermont et al. 2009). However, our findings may also support the idea that an individual’s overall pain experience is encompassed by the combined burden of their spontaneous and evoked pain types. For example, the highest functional group in our sample experienced the lowest combination of both spontaneous and evoked pains while the lowest functional group experienced the highest severity of both spontaneous and evoked pain types. Thus, the latter group had the greatest overall burden of pain, highlighting the importance of assessing both pain types in clinical and research settings. It is also interesting that differences in pain and function among these clusters closely mirrored differences in the WOMAC-pain measure. This finding may possibly indicate that this brief, validated, self-report assessment may be useful in predicting movement-evoked pain and function in clinical settings where task performance is not feasible.
Our participants with the lowest physical functional performance along with severe movement-evoked pain also reported more depressive symptoms, increased pain hypervigilance, and more pain-related catastrophizing than the other clusters. Previous studies have reported associations between psychological measures and activity-related pain (Sullivan et al. 2002; Swinkels-Meewisse et al. 2006) including associations with treatment outcomes (Lindberg et al. 2016). Indeed, multiple psychological factors in people with knee OA pain are associated with the development of disability and longer term worsening of pain (Helminen et al. 2016). On the other hand, the most important predictor of catastrophizing, anxiety and depression after total joint replacement was preoperative pain and self-reported physical function (Wood et al. 2016), supporting reciprocal complex associations between pain, psychological and physical functioning. It is possible that a set of psychological behaviors (i.e., hyper-attentiveness to pain, depression, catastrophizing) contributes to maladaptive movement avoidance and physical inactivity patterns that are similar to those proposed in the fear-avoidance model in persons with low back pain (Beneciuk et al. 2012). Future research is needed to determine whether similar patterns are present in persons with knee pain and whether targeted psychological interventions are complementary and beneficial with respect to pain and physical function.
The participants with the lowest overall physical functional performance were also the most pain sensitive to pressure, cold and punctate stimuli across several body sites. Similarly, previous research has demonstrated increased generalized pressure pain sensitivity in patients with knee OA pain, suggesting the presence of central sensitization to mechanical stimuli (Arendt-Nielsen et al. 2010; Frey-Law et al. 2016). These lower functioning participants also exhibited greater heat and mechanical temporal summation. Studies have also reported a tendency for individuals with knee OA pain to experience greater temporal summation of pain, thought to reflect pain amplification at the spinal cord (Skou et al. 2013; Arendt-Nielsen et al. 2010). That mechanical experimental pain measures differed most consistently between the functional groups likely reflects differences in joint-activated nociceptor sensitization. Indeed, movement-evoked pain is associated with sensitization of peripheral Aδ and C-fiber afferents (Brucini et al. 1981; Hendiani et al. 2003), while spontaneous pain or pain at rest is related to sensitization at the dorsal horn and spinal cord (Schaible et al., 2002). Also, increased heat temporal summation implicates centrally-mediated mechanisms, and evidence suggests that in some individuals, peripheral and central nervous system mechanisms significantly contribute to knee OA pain (Murphy et al. 2011; Arendt-Nielsen et al. 2010; Frey-Law et al. 2016; Cardoso et al. 2016). Future mechanism-based research is needed incorporating measures of temporal summation of movement-evoked pain and their associations with physical function and intervention outcomes.
The current study has some limitations. First, most of our sample was highly functional, consistent with community-dwelling individuals not necessarily seeking care for knee pain. This is further reflected by the small sample size in the lowest functional group. Thus, it is unknown whether the same analyses in more severe clinical samples would yield similar results. Studies are needed to determine whether these profiles can be replicated across different settings and samples, including the oldest old. Furthermore, treatment response across profiles such as these may provide important mechanistic and predictive information supporting a personalized medical approach.
Despite the limitations, our findings support the need for consideration of movement-evoked pain during physical performance tasks as these have the potential to increase the value of functional, clinical and experimental pain assessments. These findings may be relevant both for research in order to identify potential biological mechanisms as well as in the clinic. The identification of the biopsychosocial mechanisms driving pain burden within homogeneous groups of individuals will ultimately allow for targeted implementation of treatments. For example, it is possible that individuals such as those in the lowest functional group would benefit from a combination of surgical, pharmacological and psychological therapies to reduce movement-evoked pain and optimize physical function. Future research is needed to test such hypotheses.
Highlights.
We found significant heterogeneity in physical performance and movement-evoked pain among community-dwelling individuals with knee osteoarthritis.
Profiles based on physical performance and movement-evoked pain differed significantly in psychological and somatosensory function.
Movement-evoked pain needs to be considered clinically in persons with knee OA.
Footnotes
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References
- 1.Arendt-Nielsen L, Nie H, Laursen MB, Laursen BS, Madeleine P, Simonsen OH, Graven-Nielsen T. Sensitization in patients with painful knee osteoarthritis. Pain. 2010;149:573–81. doi: 10.1016/j.pain.2010.04.003. [DOI] [PubMed] [Google Scholar]
- 2.Bellamy N, Buchanan WW, Goldsmith CH, Campbell J, Stitt LW. Validation study of WOMAC: a health status instrument for measuring clinically important patient relevant outcomes to antirheumatic drug therapy in patients with osteoarthritis of the hip or knee. J. Rheumatol. 1988;15:1833–40. [PubMed] [Google Scholar]
- 3.Beneciuk JM, Robinson ME, George SZ. Low back pain subgroups using fear-avoidance model measures: results of a cluster analysis. Clin J Pain. 2012;28:658–66. doi: 10.1097/AJP.0b013e31824306ed. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Brucini M, Duranti R, Galletti R, Pantaleo T, Zucchi PL. Pain thresholds and electromyographic features of periarticular muscles in patients with osteoarthritis of the knee. Pain. 1981;10:57–66. doi: 10.1016/0304-3959(81)90045-2. [DOI] [PubMed] [Google Scholar]
- 5.Cardoso JS, Riley JL, 3rd, Glover T, Sibille KT, Bartley EJ, Goodin BR, Bulls HW, Herbert M, Addison AS, Staud R, Redden DT, Bradley LA, Fillingim RB, Cruz-Almeida Y. Experimental pain phenotyping in community-dwelling individuals with knee osteoarthritis. Pain. 2016;157:2104–14. doi: 10.1097/j.pain.0000000000000625. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Crawford JR, Henry JD. The positive and negative affect schedule (PANAS): construct validity, measurement properties and normative data in a large non-clinical sample. Br. J. Clin. Psychol. 2004;43:245–65. doi: 10.1348/0144665031752934. [DOI] [PubMed] [Google Scholar]
- 7.Cruz-Almeida Y, King CD, Goodin BR, Sibille KT, Glover TL, Riley JL, Sotolongo A, Herbert MS, Schmidt J, Fessler BJ, Redden DT, Staud R, Bradley LA, Fillingim RB. Psychological profiles and pain characteristics of older adults with knee osteoarthritis. Arthritis Care Res.(Hoboken.) 2013:10. doi: 10.1002/acr.22070. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Cruz-Almeida Y, Sibille KT, Goodin BR, Petrov ME, Bartley EJ, Riley JL, 3rd, King CD, Glover TL, Sotolongo A, Herbert MS, Schmidt JK, Fessler BJ, Staud R, Redden D, Bradley LA, Fillingim RB. Racial and ethnic differences in older adults with knee osteoarthritis. Arthritis Rheumatol. 2014;66:1800–10. doi: 10.1002/art.38620. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Eggermont LH, Bean JF, Guralnik JM, Leveille SG. Comparing pain severity versus pain location in the MOBILIZE Boston study: chronic pain and lower extremity function. J Gerontol A Biol Sci Med Sci. 2009;64:763–70. doi: 10.1093/gerona/glp016. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Frey-Law LA, Bohr Nl Fau - Sluka Kathleen A, Sluka Ka Fau - Herr Keela, Herr K Fau - Clark Charles R, Clark Cr Fau - Noiseux Nicolas O, Noiseux No Fau - Callaghan John J, Callaghan Jj Fau - Zimmerman M Bridget, Zimmerman Mb Fau - Rakel Barbara A, Rakel BA. Pain sensitivity profiles in patients with advanced knee osteoarthritis. 2016 doi: 10.1097/j.pain.0000000000000603. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Guralnik JM, Ferrucci L, Simonsick EM, Salive ME, Wallace RB. Lower-extremity function in persons over the age of 70 years as a predictor of subsequent disability. N. Engl. J. Med. 1995;332:556–61. doi: 10.1056/NEJM199503023320902. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Helminen EE, Sinikallio SH, Valjakka AL, Vaisanen-Rouvali RH, Arokoski JP. Determinants of pain and functioning in knee osteoarthritis: a one-year prospective study. 2016 doi: 10.1177/0269215515619660. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Hendiani JA, Westlund KN, Lawand N, Goel N, Lisse J, McNearney T. Mechanical sensation and pain thresholds in patients with chronic arthropathies. J. Pain. 2003;4:203–11. doi: 10.1016/s1526-5900(03)00557-1. [DOI] [PubMed] [Google Scholar]
- 14.Hopman-Rock M, Odding E Fau - Hofman A, Hofman A Fau - Kraaimaat FW, Kraaimaat Fw Fau - Bijlsma JW, Bijlsma JW. Physical and psychosocial disability in elderly subjects in relation to pain in the hip and/or knee. 1996 [PubMed] [Google Scholar]
- 15.Jinks C, Jordan K Fau - Croft P, Croft P. Osteoarthritis as a public health problem: the impact of developing knee pain on physical function in adults living in the community: (KNEST 3) 2007 doi: 10.1093/rheumatology/kem013. [DOI] [PubMed] [Google Scholar]
- 16.King CD, Sibille KT, Goodin BR, Cruz-Almeida Y, Glover TL, Bartley E, Riley JL, Herbert MS, Sotolongo A, Schmidt J, Fessler BJ, Redden DT, Staud R, Bradley LA, Fillingim RB. Experimental pain sensitivity differs as a function of clinical pain severity in symptomatic knee osteoarthritis. Osteoarthritis. Cartilage. 2013;21:1243–52. doi: 10.1016/j.joca.2013.05.015. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Lindberg MF, Miaskowski C, RustoEn T, Rosseland LA, Cooper BA, Lerdal A. Factors that can predict pain with walking, 12 months after total knee arthroplasty. 2016 doi: 10.1080/17453674.2016.1237440. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Mankovsky-Arnold T, Wideman TH, Lariviere C, Sullivan MJ. Measures of spontaneous and movement-evoked pain are associated with disability in patients with whiplash injuries. 2014 doi: 10.1016/j.jpain.2014.06.010. [DOI] [PubMed] [Google Scholar]
- 19.McCracken LM. "Attention' to pain in persons with chronic pain: a behavioural approach. Behavior Therapy. 1997;28:271–84. [Google Scholar]
- 20.Mobasheri A, Matta C, Zákány R, Musumeci G. Chondrosenescence: definition, hallmarks and potential role in the pathogenesis of osteoarthritis. Maturitas. 2015 Mar;80(3):237–44. doi: 10.1016/j.maturitas.2014.12.003. Epub 2014 Dec 24. [DOI] [PubMed] [Google Scholar]
- 21.Murphy SL, Lyden AK, Phillips K, Clauw DJ, Williams DA. Subgroups of older adults with osteoarthritis based upon differing comorbid symptom presentations and potential underlying pain mechanisms. Arthritis Res Ther. 2011;13:R135. doi: 10.1186/ar3449. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Musumeci G, Szychlinska MA, Mobasheri A. Age-related degeneration of articular cartilage in the pathogenesis of osteoarthritis: molecular markers of senescent chondrocytes. Histol Histopathol. 2015 Jan;30(1):1–12. doi: 10.14670/HH-30.1. Epub 2014 Jul 10. [DOI] [PubMed] [Google Scholar]
- 23.Neogi T, Felson D Fau - Niu Jingbo, Niu J Fau - Nevitt Michael, Nevitt M Fau - Lewis Cora E, Lewis Ce Fau - Aliabadi Piran, Aliabadi P Fau - Sack Burt, Sack B Fau - Torner James, Torner J Fau - Bradley Lawrence, Bradley L Fau - Zhang Yuqing, Zhang Y. Association between radiographic features of knee osteoarthritis and pain: results from two cohort studies. 2009 doi: 10.1136/bmj.b2844. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Perera S, Mody SH, Woodman RC, Studenski SA. Meaningful change and responsiveness in common physical performance measures in older adults. 2006 doi: 10.1111/j.1532-5415.2006.00701.x. [DOI] [PubMed] [Google Scholar]
- 25.Radloff L. The CES-D scale: A self-report depression scale for research in the general population. Journal of Applied Psychological Measurement. 1977;1:385–401. [Google Scholar]
- 26.Robinson ME, Riley JL, III, Myers CD, Sadler IJ, Kvaal SA, Geisser ME, Keefe FJ. The Coping Strategies Questionnaire: a large sample, item level factor analysis. Clin. J. Pain. 1997;13:43–49. doi: 10.1097/00002508-199703000-00007. [DOI] [PubMed] [Google Scholar]
- 27.Roelofs J, Peters ML, McCracken L, Vlaeyen JW. The pain vigilance and awareness questionnaire (PVAQ): further psychometric evaluation in fibromyalgia and other chronic pain syndromes. Pain. 2003;101:299–306. doi: 10.1016/S0304-3959(02)00338-X. [DOI] [PubMed] [Google Scholar]
- 28.Schaible HG, Ebersberger A, Von Banchet GS. Mechanisms of pain in arthritis. Ann N Y Acad Sci. 2002;966:343–54. doi: 10.1111/j.1749-6632.2002.tb04234.x. [DOI] [PubMed] [Google Scholar]
- 29.Sharma L, Cahue S, Song J, Hayes K, Pai YC, Dunlop D. Physical functioning over three years in knee osteoarthritis: role of psychosocial, local mechanical, and neuromuscular factors. Arthritis Rheum. 2003;48:3359–70. doi: 10.1002/art.11420. [DOI] [PubMed] [Google Scholar]
- 30.Skou ST, Graven-Nielsen T, Rasmussen S, Simonsen OH, Laursen MB, Arendt-Nielsen L. Widespread sensitization in patients with chronic pain after revision total knee arthroplasty. Pain. 2013;154:1588–94. doi: 10.1016/j.pain.2013.04.033. [DOI] [PubMed] [Google Scholar]
- 31.Sullivan MJ, Rodgers WM, Kirsch I. Catastrophizing, depression and expectancies for pain and emotional distress. Pain. 2001;91:147–54. doi: 10.1016/s0304-3959(00)00430-9. [DOI] [PubMed] [Google Scholar]
- 32.Sullivan MJ, Rodgers WM, Wilson PM, Bell GJ, Murray TC, Fraser SN. An experimental investigation of the relation between catastrophizing and activity intolerance. Pain. 2002;100:47–53. doi: 10.1016/s0304-3959(02)00206-3. [DOI] [PubMed] [Google Scholar]
- 33.Swinkels-Meewisse IE, Roelofs J, Oostendorp RA, Verbeek AL, Vlaeyen JW. Acute low back pain: pain-related fear and pain catastrophizing influence physical performance and perceived disability. 2006 doi: 10.1016/j.pain.2005.10.005. [DOI] [PubMed] [Google Scholar]
- 34.van Dijk GM, Dekker J Fau - Veenhof Cindy, Veenhof C Fau - van den Ende Cornelia HM, van den Ende CH. Course of functional status and pain in osteoarthritis of the hip or knee: a systematic review of the literature. 2006 doi: 10.1002/art.22244. [DOI] [PubMed] [Google Scholar]
- 35.Von Korff M, Ormel J, Keefe FJ, Dworkin SF. Grading the severity of chronic pain. Pain. 1992;50:133–49. doi: 10.1016/0304-3959(92)90154-4. [DOI] [PubMed] [Google Scholar]
- 36.Watson D, Clark LA, Tellegen A. Development and validation of brief measures of positive and negative affect: the PANAS scales. Journal of Personality & Social Psychology. 1988;54:1063–70. doi: 10.1037//0022-3514.54.6.1063. [DOI] [PubMed] [Google Scholar]
- 37.Wood TJ, Thornley P, Petruccelli D, Kabali C, Winemaker M, de Beer J. Preoperative Predictors of Pain Catastrophizing, Anxiety, and Depression in Patients Undergoing Total Joint Arthroplasty. 2016 doi: 10.1016/j.arth.2016.05.056. LID - S0883-5403(16)30235-2 [pii] LID - 10.1016/j.arth.2016.05.056 [doi] [DOI] [PubMed] [Google Scholar]
- 38.Zakoscielna KM, Parmelee PA. Pain variability and its predictors in older adults: depression, cognition, functional status, health, and pain. 2013 doi: 10.1177/0898264313504457. [DOI] [PubMed] [Google Scholar]